Companies that want to implement a data warehousing solution to organize and utilize business data more effectively, institute cross functional systems and align information technology and corporate goals. This Reference Architecture allows customers to make informed decisions for competing successfully in a rapidly changing business environment. This architecture addresses the needs of the very large data warehouse (more than a TB of data) customers within a tight IT budget by reducing the total cost of ownership of a data warehousing infrastructure.
This architecture also addresses infrastructure technology requirements that are common to Business Intelligence solutions in many vertical markets such as financial services, telecommunications, manufacturing, retail, and healthcare.
The Enterprise Data Warehouse Reference Architecture addresses the main tier of the complete Data Warehouse/Business Intelligence (DW/BI) solution: the central data warehouse. This tier stores and manages consolidated data, runs queries on it, and makes it available to various data marts. Customers can implement this reference architecture as is, or change it depending on their business requirements, with service and support from Sun Professional Services and others.
Enterprises have spent last three to four years implementing OLTP, ERP, CRM, and SCM systems. They are collecting large amounts of data from these sources, and need to get a complete picture of their entire business operations. DW/BI allows these enterprises to stay competitive and to react to market forces very quickly. More specifically, the Enterprise Data Warehouse Reference Architecture:
Solves Very Large Database (VLDB) problems in a radical new approach, providing real-time analysis of years of data, instead of months of data, for example.
Allows customers to retrofit to a VLDB solution within an existing IT budget while reducing time to deployment.
Provides 98 percent linear scalability of software and hardware based on industry-leading scalable SPARC[r] architecture and Solaris Operating Environment, i.e. 1-100+ processors in a single node.
Improves query speed on data loads up to 1000x verses typical data warehouse solutions.
Reduces storage needs up to 75 percent verses typical data warehouse solutions.
